2.1 Blended Learning Experiences

The term blended learning has been defined in 2006 by Graham as "The combination of instruction from two historically separate models of teaching and learning: traditional face-to-face learning systems and computer-supported learning environments" (^{Graham, 2006}).

The blended learning systems intend to overcome the failures of e-learning systems: most current e-learning approaches focus on solving digital content management problems and neglect learning processes and theories. Besides instructors on e-learning systems have to develop social, teaching and technical skills. In this respect, some instructors do not have the time, knowledge or motivation to use e-learning systems.

There are several different reasons for executing blended learning experiences in both academic and corporate fields. According to several researchers there are three important reasons for selecting a blended learning experience instead of other learning options (^{Derntl and Motschnig-Pitrik, 2005}; ^{Graham, 2006}).

Firstly, blended learning experiences help to implement teaching practices more effectively. Blended learning intends to solve some of the problems of the face-to-face learning model, such as, the mere transmission of knowledge, specifically when the instructors transmit the knowledge and the students do not participate in an active way.

Secondly, the accessibility and flexibility are very important factors in blended learning, because the students can combine the flexibility of computer-supported learning environments with the social interactions in the face-to-face model. This flexibility is associated with the fact that the students and instructors can interact through the learning environments without neither time nor space constraints.

And finally the blended learning experiences provide universities and companies with economic benefits because they offer the opportunity to obtain a large return on investment. Moreover, the costs of several elements in particular, such as physical infrastructure, technological resources, etc. are decreased.

There are several studies that corroborate the use of blended learning as a successful approach. An example is the research study developed at the University of Rijeka, Croatia where a blended learning model was used as a mixture of collaborative learning, problem-based learning (PBL) and independent learning, in a "Teaching Methods in Information Science" course. This model was implemented as a combination of a face-to-face environment and online learning using a learning management system called adaptive hypermedia courseware (AHyCo) (^{Hoic-Bozic, Mornar and Boticki, 2009}).

Other study presented in (^{Alonso et al., 2011}) showed the evaluation of a blended learning approach in a software engineering related course unit as part of an under-graduate engineering degree program in computing. The aim of this research study was to decrease the underachievement and the high course unit dropout rate in the past courses. The results of this experience showed the effectiveness of the new system deployed compared to the lecture-based system previously (^{Alonso et al., 2011}).

Additional to mentioned studies, there are several models and initiatives to develop blended learning experiences.

The BLESS (blended learning systems structure) model was developed as a framework for mining, applying, evaluating, and improving blended, person-centered learning scenarios. This model is integrated by six layers: i) learning theory and didactic baseline: it sets the overall educational targets, resulting interpersonal attitudes, the delivers requirements and constraints on the technological solution; ii) blended learning courses: it applies the didactic orientation defined in the previous layer; iii) course scenarios: it provides conceptual models and visualizations of scenarios by modeling their sequences as activity diagrams in the standard Unified Modeling Language (UML) notation; iv) blended learning patterns: they include online knowledge gathering and construction in groups, publishing of electronic content and interactive elements; v) web templates: it shows parameterized and interactive web pages; and vi) learning platform: it contains the web templates and the included patterns (^{Derntl and Motschnig-Pitrik, 2005}).

The teaching system called BLOSSOMS (Blended Learning Open Source Science or Math Studies) is an initiative to develop free repository of blended-learning video modules for high school math and science classes, created by gifted volunteer educators from around the world. These modules were designed to offer learning exercises that will enhance critical thinking skills and retain students' interest in math and science. The high school BLOSSOMS initiative is conducted by the following considerations: i) technology is changing education; ii) the Open Educational Resources (OERs) are free learning materials; iii) the World is creating major environments on the web; iv) many high school students, are turned off to studying math and science; v) the instructors in high schools need appropriate technology; vi) generally the teaching of mathematics in high schools is done formally. And vii) the motivation can increase the numbers who will select engineering, science and mathematics as career goals (^{Larson and Murray, 2008}).

2.2 The Motivation in Learning Environments

According to some researchers there are different definitions of motivation, we present below two of them:

Motivation is an internal state or condition that serves to activate or to energize the human behavior. The sources of the motivation can be internal: interest, enjoyment, etc., or external: get a degree, fear of punishment or sanctions, among others (^{Weiner, 1985}; ^{Graham and Weiner, 1996}; ^{HersX hkovitz and Nachmias, 2009}).

Motivation is the magnitude and direction of the behavior. In other words it refers to the decisions that people make about the experiences that they do or avoid, and the degree of effort made in this direction (^{Keller, 1983}, ²⁰⁰⁸).

The motivation is very complex. More specifically, the students' motivation in learning environments is of scientific significance. Some authors use the concept of "motivational factors" to analyze a set of theories, studies and models to improve students' motivation (^{Keller, 1983}, ²⁰⁰⁸; ^{Weiner, 1985}; ^{Cocea and Weibelzahl, 2009}; ^{Figas, Hagel and Bartel, 2013}; ^{Naves et al., 2013}; ^{Muñoz-Merino et al., 2014}).

In the literature reviewed we found that the motivational design models can be categorized into four groups: i) person-centered models; ii) environmentally-centered models; iii) interaction-centered models and iv) omnibus models (^{Keller, 2008}). Nowadays, interaction-centered models are probably the most used in the study of human learning and motivation in an educational field. Some examples of this type of models are the Wlodkowsky model (^{Wlodkowski, 2010}) and the ARCS model (^{Keller, 1983}, ²⁰⁰⁸).

The Wlodkowsky model provides an approach that includes a large number of motivational factors. This model divides motivational strategies into six categories: attitudes, needs, stimulation, affect, competence and reinforcement (^{Wlodkowski, 2010}).

And the ARCS (attention, relevance, confidence and satisfaction) model has a complete motivational design process for developing motivational strategies.

We based our research on the ARCS model because this has been tested and accepted as a successful one for implementing applications on motivational interventions as discussed in (^{Keller, 2008}).

The ARCS model has four components: attention, relevance, confidence and satisfaction. Each component is associated with the "principles of motivation to learn" defined in (^{Keller, 1983}). Additionally, each ARCS component can be used to determine the students' motivational factors that need to be identified in order to improve their motivation to learn.

3.1 Description

The Motivation Booster was implemented by developing software components that analyze the interactions of the students with the system and then give feedback information to the students and instructors. This information associated with the collaborative learning activities carried out by the students are motivational messages. Every message is a congratulation or a recommendation message depending on the progress the collaborative learning activities that the students have completed. They are showed in two ways: on-line and out-of-system.

On-line: The system displays through a graphical user interface motivational messages to the students and instructors about the progress of the collaborative learning activities.

Out-of-system: the motivational messages are sent via e-mail.

The general Motivation Booster architecture is based on a Web server framework, composed of five interconnected elements:

The activities repository: stores the script implemented by the instructor. S/he defines the collaborative learning activities that are performed by the students while interacting with the system.

The data model: contains the information about students' interactions with Moodle system. This information is stored in the database or in the system log files.

The data processing service: receives and processes the statistical reports on the activities performed by the students.

The trigger rules manager: is based on two types of general rules: i) rules related to learning activities completed in due time, and ii) rules related to sequence of learning activities. The trigger rules manager is able to generate the congratulation and recommendation messages.

The feedback information service: displays on-line motivational messages, and sends the same information via e-mail (out-of-system).

3.2 Description of the implementation in Moodle

Moodle can be distributed through GNU licensing. The word Moodle was originally an acronym standing for modular object-oriented dynamic learning environment. This tool is extremely useful for educational programmers and scholars (^{Moodle, 2019}).

This software can be used to create Internet-based courses and websites where instructors and students can interact. Moodle can be employed not only to prepare but also to teach such courses, because this platform also provides administration and communication tools. Moodle is not a full collaborative system; however, in the present study we have selected it as a system to support collaborative learning activities because Moodle has been widely used in university courses. Furthermore this system provides standardized components to add new functionalities (^{Garcia-Penalvo et al., 2011}). These components are modules and plugins embedded in the system. Moodle supports different kinds of plugins.

The modules and plugins provide the main tools to support learning activities in Moodle using the educational resources. The instructor can select the tools that he or she needs to use in a specific course such as: forums, chats, messages services, etc.

As we mentioned, Moodle is not a collaborative system. Nevertheless we have added functionalities of collaborative learning to this system. For this purpose, we have selected a previous module in Moodle called "database activity module". This module only supports interactions between students and instructor. And from the previous module we have developed a new module to assist additionally students-to-students interactions. This new activity module allows for the instructor and/or students to perform and display different collaborative tasks about any topic. Three specific tasks in the developed module were implemented: i) build an entry (one entry is defined like a document added by the students and the instructors into the system); ii) make comments on classmates' entries and iii) rate other classmates' entries. Additionally, we designed a "block" plugin to implement the Motivation Booster as an innovative feedback information service. It is important to remark that the Moodle Relational Schema was modified. More details about the implementation of the Motivation Booster in Moodle are in (^{Echeverría, 2011}; ^{Echeverria, 2017}).

4.1 Hypotheses

H1: The motivational messages sent by the booster affect the students' interactions when they perform the collaborative learning activities. Specifically, these messages can increase the interactions with the system.

H2: The motivational messages help to determine the students' motivational factors.

4.2 Participants of blended learning experiences

Two blended learning experiences were put into practice at the UPB-Montería (Colombia) over an academic year with students enrolled in the course called "Software Engineering" at the Computer Science Department. Seventeen students (control group) participated in the first blended learning experience, where they used the Moodle system without the Motivation Booster. Sixteen students (experimental group) participated in the second blended learning experience, where they used the Moodle system with the Motivation Booster implemented.

4.3 Instruments

In this study, the students' interactions were analyzed, which are the dependent variables recorded in the system. Besides, one individual questionnaire was applied to students that participated in the experimental group. The aim was to know the students' motivational factors when they received the congratulation and the recommendation messages. These data allowed us to analyze the impact of the Motivation Booster in the blended learning experiences and to draw these factors.

The students' motivational factors in this study are assigned to the ARCS components in each type of message. These motivational factors have been developed conceptually in (^{Echeverría, 2011}; ^{Echeverria, 2017}) and they have been tested empirically.

Regarding congratulation messages, the impact of the Motivation Booster was evaluated considering three motivational components of the ARCS model: relevance, confidence and satisfaction. From these components were measured nine students' motivational factors:

The motivational factors related to the relevance component are: i) the student feels his/her performance improved, ii) the student feels involved in collaborative activities and iii) the student feels interested in the content.

The motivational factors related to the confidence component are: i) the student feels s/he is achieving his/her goals, ii) the student feels self-assured and iii) the student feels successful.

The motivational factors related to the satisfaction component are: i) the student feels his/her work is recognized, ii) the student feels treated fairly and iii) the student feels enthusiastic.

Regarding the recommendation messages, the impact of the Motivation Booster was evaluated considering three motivational components of the ARCS model: attention, relevance and confidence. From these components were measured nine students' motivational factors. The motivational factors related to the relevance component and the confidence one are the same motivational factors mentioned above.

The motivational factors related to the attention component are: i) the student feels always informed, ii) the student feels mentally stimulated and iii) the student feels curiosity.

4.4 Procedure

The same instructional script was proposed in the two mentioned experiences. On the one hand, the students spent four hours per week in traditional face-to-face learning. And on the other hand, the students and instructors used the Moodle system across all the blended learning experiences to complete the collaborative learning activities in several topics. The instructors advised students to use the system for two hours per week to complete these activities.

The activities scripted by the instructors and performed by the students were: i) build an entry, ii) write comments on classmates' entries, and iii) rate other classmates' entries. From these activities, three variables related to students' interactions were defined in Moodle: i) total number of submitted entries, ii) total number of submitted comments and iii) total number of submitted ratings.